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IPPS
2000
IEEE
15 years 9 months ago
PaDDMAS: Parallel and Distributed Data Mining Application Suite
Discovering complex associations, anomalies and patterns in distributed data sets is gaining popularity in a range of scientific, medical and business applications. Various algor...
Omer F. Rana, David W. Walker, Maozhen Li, Steven ...
ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 6 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
KDD
2007
ACM
186views Data Mining» more  KDD 2007»
16 years 5 months ago
An Ad Omnia Approach to Defining and Achieving Private Data Analysis
We briefly survey several privacy compromises in published datasets, some historical and some on paper. An inspection of these suggests that the problem lies with the nature of the...
Cynthia Dwork
PODS
2003
ACM
156views Database» more  PODS 2003»
16 years 5 months ago
Limiting privacy breaches in privacy preserving data mining
There has been increasing interest in the problem of building accurate data mining models over aggregate data, while protecting privacy at the level of individual records. One app...
Alexandre V. Evfimievski, Johannes Gehrke, Ramakri...
153
Voted
ECCV
2010
Springer
15 years 5 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof